Improving the wisdom of crowds

A new approach to predicting the outcomes of major events could give people an incentive to seek out more diverse sources of information, according to a new study.

Market economies and democracies rely on what is referred to
as crowd intelligence, or the wisdom of crowds. This is the idea that large
groups know more about what is best than a single individual. This knowledge is
the basis for stock markets, betting exchanges and special investment vehicles
called prediction markets.

However, a new study led by
Dr Richard Mann from the School of Mathematics at Leeds highlights the recent failing of prediction markets in a number of high profile
events, including last year's Brexit referendum and US presidential election.

Consistent inaccuracies about such events points to possible
flaws in the assumptions made about crowd intelligence. The study suggests the
lack of diverse information sources among decision-making individuals has contributed to this failure
in prediction markets, and may also
undermine other collective endeavours such as academia and democracies

Dr Mann and Professor Dirk Helbing at ETH Zurich have
developed a new theoretical model that overcomes this problem by giving people
an incentive to seek out new sources of information, and an extra reason to
share it.

In this new prediction market system, people
would only be rewarded if they expressed accurate views but were also in the
minority.

This "minority rewards" system
encourages groups to bring together wider sets of information, leading to more
accurate collective decisions.

In an article written for The Conversation, Dr Mann
describes his "minority rewards" model and gives insight into why current forms of collective decision-making may be prone
to failure.